Hire pre-vetted LLM engineers for retrieval-augmented generation, fine-tuning, AI agents and
evaluation. Move from demo to dependable product with engineers who have shipped LLM features to
real users. First profiles in 48 hours.
Our LLM developers build retrieval pipelines, fine-tune open models, design evaluation sets
and deploy LLM features with guardrails. Browse sample profiles below, then tell us your use
case.
Sagar P.
Sr. LLM Developer
Super Dev
$25/hour
4.8
Sagar has 7 years of
experience developing and fine-tuning...
Sagar has 7 years of experience developing and fine-tuning language models for healthcare
and finance applications. His data collection and annotation expertise ensures
high-quality inputs for accurate predictive modelling.
Shridhar brings 6 years of
experience and specializes in applying...
Shridhar brings 6 years of experience and specializes in applying NLP techniques to
enhance customer experiences in the e-commerce and retail sectors. His proficiency in
unsupervised learning and data pre-processing makes him adept at handling complex
datasets.
Anjali has 8 years of
experience in sentiment analysis and topic...
Anjali has 8 years of experience in sentiment analysis and topic modeling, particularly
within the finance and legal industries. Her use of advanced NLP libraries ensures precise
and actionable insights from large text datasets.
Brijesh has over 4 years of
experience in machine translation...
Brijesh has over 4 years of experience in machine translation and data augmentation
techniques, focusing on creating multilingual educational tools and travel applications to
enhance user experiences across different languages.
Lalit is skilled in
creating interpretable models and visualizing...
Lalit is skilled in creating interpretable models and visualizing complex data,
particularly in healthcare and real estate. With 6 years of experience, his focus on model
interpretability ensures that AI solutions are transparent and reliable.
Vikram brings 5 years of
experience in text classification...
Vikram brings 5 years of experience in text classification and entity recognition, with
significant experience in the finance and HR sectors. His work helps streamline operations
by automating data extraction and analysis.
Bharti has 7 years of
experience in developing dialogue systems...
Bharti has 7 years of experience in developing dialogue systems and leveraging contextual
embeddings to enhance customer service and entertainment applications. Her innovative
solutions improve user interactions and satisfaction.
With 6 years of experience,
Bhavesh specializes in natural...
With 6 years of experience, Bhavesh specializes in natural language generation and LLM
development, with a focus on the healthcare and education industries. His work in
developing AI-driven solutions enhances patient care and educational tools through
advanced language models.
Our LLM developers have taken chatbots, copilots and document assistants live. They
know how to handle hallucinations, slow responses and rising token bills.
Clean, Tested Code
Every LLM engineer writes tested, documented code for prompts, retrieval and model
calls, so your team can maintain it after handover.
Model-Agnostic Choices
Our developers work with GPT, Claude, Gemini, Llama and Mistral and pick the right
model for your accuracy, privacy and budget needs.
Easy Integration
We connect LLMs to your CRM, knowledge base, databases and internal tools through
secure APIs and vector databases.
Measured Quality
Our engineers build evaluation sets and automated tests, so answer quality is
measured before and after every release.
Lower Inference Costs
Caching, model routing, quantisation and self-hosting with vLLM keep latency and
token spend under control as usage grows.
Enhanced Data Security
NDA and IP agreements, PII redaction, prompt-injection defence and private or
self-hosted models when data cannot leave your environment.
Our LLM developers have taken chatbots, copilots and document assistants live.
They know how to handle hallucinations, slow responses and rising token bills.
Every LLM engineer writes tested, documented code for prompts, retrieval and
model calls, so your team can maintain it after handover.
Our developers work with GPT, Claude, Gemini, Llama and Mistral and pick the
right model for your accuracy, privacy and budget needs.
We connect LLMs to your CRM, knowledge base, databases and internal tools
through secure APIs and vector databases.
Our engineers build evaluation sets and automated tests, so answer quality is
measured before and after every release.
Caching, model routing, quantisation and self-hosting with vLLM keep latency
and token spend under control as usage grows.
NDA and IP agreements, PII redaction, prompt-injection defence and private or
self-hosted models when data cannot leave your environment.
Struggling to Hire LLM Engineers? We Have Them Ready
LLM engineers who have shipped real products are scarce and expensive to find on your own.
Our network gives you vetted LLM developers in days, not months.
Profiles in 48 Hours
Share your use case and receive vetted LLM developer profiles within 48 hours.
Drop-off Ratio < 1%
At Supersourcing, we take pride in our less than 1% drop-off ratio of LLM developers
for hire, which ensures that you find the perfect fit for your hiring needs.Fewer than
1% of selected LLM developers drop off before joining, so your roadmap stays on track.
AI-Powered Screening
Our AI matching engine filters candidates by model stack and use case before a recruiter
reviews them.
Dedicated Account
Manager
One point of contact for onboarding, replacements and scaling your LLM team.
Hire LLM developers in 4 Simple Steps!
Tell us what you are building, whether a chat assistant, document search, an agent workflow or a
fine-tuned model, and meet matched LLM engineers within 48 hours.
Describe Your Use Case
Share the problem, your data and
your model stack on a short call.
Get Matched LLM Developers
Review vetted profiles with
direct experience in your use case.
Interview Your Shortlist
Discuss architecture, review
past work and pick your engineer.
Start Building
We handle contracts, IP
agreements and compliance while your engineer starts delivering.
Flexible Ways to
Hire LLM Engineers
Start with a proof of concept, keep a dedicated LLM engineer for the long term, or hire permanently.
Contract
Hire an LLM developer on contract for a proof of concept or fixed-scope build. We handle
payroll and compliance.
Supersourcing is an AI recruitment
platform that skips CV screening and long interview rounds. Hire one LLM engineer or a
full generative AI team and save up to 90% of your hiring time.
What Are the Business Benefits of Large Language Models?
What Challenges Do LLM Developers Solve?
What Skills Should You Look For When Hiring LLM Developers?
What
Does an LLM Developer Do?
An LLM developer builds
products on large language models: chat assistants, document search, AI agents and
content tools. The work covers retrieval pipelines, prompt and tool design,
fine-tuning, evaluation, guardrails and cost control, so the feature works reliably for
real users, not just in a demo.
What Is
LLM Fine-Tuning, and When Do You Need It?
Fine-tuning trains an existing model further on your own examples so it learns your
domain language, format or tone. It suits fixed tasks such as classification,
extraction or a consistent writing style. When answers must come from documents that
change often, retrieval-augmented generation (RAG) is usually the better first step.
Many products combine both.
How Do LLM
Developers Improve Sentiment Analysis?
LLMs read context, sarcasm and mixed opinions far better than keyword-based tools. LLM
developers design prompts or fine-tune smaller models to score sentiment by topic, then
connect results to dashboards, so support, product and marketing teams see what
customers actually feel.
What Are the
Business Benefits of Large Language Models?
Faster customer support with assistants that answer from your own knowledge base.
Hours saved on reading, summarising and drafting documents.
Better search across contracts, tickets and internal wikis
New product features, such as copilots and smart forms, that set you apart.
What
Challenges Do LLM Developers Solve?
Hallucinations:
fixed with better retrieval, grounded prompts and citation checks
Rising costs:
controlled with caching, model routing and smaller models where possible.
Slow responses:
improved with streaming, batching and optimised inference.
Data privacy:
handled with PII redaction and private or self-hosted models.
Unclear quality:
measured with evaluation datasets and regression tests.
What Skills
Should You Look For When Hiring LLM Developers?
Strong Python skills and
experience with LLM APIs; many teams also hire Python
developers to build the backend around the model.
Hands-on RAG works with
vector databases and embeddings.
Fine-tuning experience
with open models.
An evaluation mindset:
test sets, metrics and regression checks.
Shipped LLM features with
real users, not only prototypes. For wider machine learning, NLP or computer vision
work, you can also hire
AI developers.
See What Our Clients Have to Say
Andile Ngcaba
Chairman at Convergence Partners
Investments
“I recently had an opportunity
to
work with Supersourcing when I was hiring for my company. It was a great experience!
They have such a wide variety of qualified React engineers , and they
responded to my request very quickly.”
Sarika SL
PeopleOps Manager at OkCredit
“We thought hiring 100+
engineers
would be extremely hard, but the team at Supersourcing was able to deliver on
time
with no hiccups. All of the engineers were experienced and good communicators.
Post sales support is also amazing.”
Subhash Gupta
Ex Vice President, Paytm
Mohamed Meman
CEO of Payload
Pramod Venkatesh
Group CTO at INQ
“We want to outsource one
product
development part, we were not looking for freelancers, already burnt our hand on
freelancers.
I checked the platform, contacted a couple of teams, good curation is done, we decided to
go
with one. Highly recommended, this is 10X better than other freelance platforms available
in
the market, with no commission."
Yes. Our LLM developers fine-tune open models, build RAG pipelines on your data
and tune prompts and guardrails, so outputs match your domain, tone and accuracy
needs.
Fintech, healthcare, legal, e-commerce, education, HR tech and SaaS. We match you
with engineers who have built LLM features in your industry where possible.
You receive matched LLM developer profiles within 48 hours. Most engineers start
within one to two weeks of selection.
LLM developer rates through Supersourcing typically range from $25 to $45 per
hour, based on the profiles shown on this page, depending on experience and
specialisation.
Candidates are reviewed on shipped LLM work, complete a RAG and evaluation task,
and pass an architecture interview with a senior AI engineer before you meet
them.
Top 20 Indian Startups of 2024
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Startups Accelerator: AI First 2024
Super Dev
$25/hour
4.8
Top Hire
4.0
4.2
4.8
350+ Large
Comp.
Partnered
